Xiaohui Wu

4.8k total citations · 1 hit paper
85 papers, 3.5k citations indexed

About

Xiaohui Wu is a scholar working on Molecular Biology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Xiaohui Wu has authored 85 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 13 papers in Genetics and 12 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Xiaohui Wu's work include Renal and related cancers (14 papers), CRISPR and Genetic Engineering (7 papers) and Adipose Tissue and Metabolism (7 papers). Xiaohui Wu is often cited by papers focused on Renal and related cancers (14 papers), CRISPR and Genetic Engineering (7 papers) and Adipose Tissue and Metabolism (7 papers). Xiaohui Wu collaborates with scholars based in China, United States and Philippines. Xiaohui Wu's co-authors include Tian Xu, Yuan Zhuang, Min Han, Sheng Ding, Gang Li, Rener Xu, Xiaochang Zhang, Xiao‐bing Yuan, Kai Lei and Pasko Rakić and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Xiaohui Wu

84 papers receiving 3.5k citations

Hit Papers

Efficient Transposition of the piggyBac (PB) Transposon i... 2005 2026 2012 2019 2005 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xiaohui Wu China 27 2.5k 593 440 409 375 85 3.5k
Gregory S. Yochum United States 28 2.2k 0.9× 529 0.9× 365 0.8× 425 1.0× 548 1.5× 87 3.6k
Jean Charron Canada 30 2.1k 0.8× 481 0.8× 350 0.8× 341 0.8× 343 0.9× 63 3.3k
Valerie Christiaens Belgium 26 2.1k 0.9× 371 0.6× 224 0.5× 449 1.1× 378 1.0× 39 3.0k
Jaesang Kim South Korea 28 2.3k 0.9× 417 0.7× 419 1.0× 469 1.1× 765 2.0× 63 3.8k
Alfredo Ciccodicola Italy 36 3.3k 1.3× 1.1k 1.8× 429 1.0× 466 1.1× 220 0.6× 101 4.4k
Hsiao‐Huei Chen Canada 31 1.9k 0.8× 981 1.7× 289 0.7× 240 0.6× 310 0.8× 73 3.2k
Yoko Itō Japan 33 2.3k 0.9× 576 1.0× 453 1.0× 457 1.1× 342 0.9× 89 3.7k
Seok‐Yong Choi South Korea 24 2.4k 1.0× 317 0.5× 448 1.0× 236 0.6× 276 0.7× 75 3.6k
Dietmar Zechner Germany 23 2.5k 1.0× 266 0.4× 621 1.4× 327 0.8× 283 0.8× 71 3.7k
Bjørn Steen Skålhegg Norway 36 2.6k 1.0× 403 0.7× 432 1.0× 233 0.6× 888 2.4× 125 4.3k

Countries citing papers authored by Xiaohui Wu

Since Specialization
Citations

This map shows the geographic impact of Xiaohui Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaohui Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohui Wu more than expected).

Fields of papers citing papers by Xiaohui Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaohui Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaohui Wu. The network helps show where Xiaohui Wu may publish in the future.

Co-authorship network of co-authors of Xiaohui Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaohui Wu. A scholar is included among the top collaborators of Xiaohui Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaohui Wu. Xiaohui Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Mei, et al.. (2023). Clinical characteristics and risk factors for tigecycline‐induced pancreatitis in a tertiary hospital: A retrospective study. British Journal of Clinical Pharmacology. 89(9). 2788–2797. 3 indexed citations
2.
Shi, Ming, Guicheng Wang, Lei Lei, et al.. (2023). An miRNA-mRNA integrative analysis in human placentas and mice: role of the Smad2/miR-155-5p axis in the development of fetal growth restriction. Frontiers in Bioengineering and Biotechnology. 11. 1159805–1159805. 5 indexed citations
4.
Wu, Xiaohui, Jianqiang Li, Fan Yang, et al.. (2021). Histone H3 methyltransferase Ezh2 promotes white adipocytes but inhibits brown and beige adipocyte differentiation in mice. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1866(6). 158901–158901. 12 indexed citations
5.
Li, Yaxin, Lihong Tan, Shanshan Xue, et al.. (2021). Disruption of Gen1 causes ectopic budding and kidney hypoplasia in mice. Biochemical and Biophysical Research Communications. 589. 173–179. 3 indexed citations
6.
Zhang, Wenting, Xiaohui Wu, Jing Wu, et al.. (2021). Systemic Overexpression of GDF5 in Adipocytes but Not Hepatocytes Alleviates High‐Fat Diet‐Induced Nonalcoholic Fatty Liver in Mice. Canadian Journal of Gastroenterology and Hepatology. 2021(1). 8894685–8894685. 3 indexed citations
7.
Chen, Shu & Xiaohui Wu. (2021). Codonopsis Radix modulates water and electrolytes homeostasis in mice. Heliyon. 7(4). e06735–e06735. 5 indexed citations
8.
Zhang, Ya, Xin Zhang, Xiaowen Wang, et al.. (2019). Gen1 Modulates Metanephric Morphology Through Retinoic Acid Signaling. DNA and Cell Biology. 38(3). 263–271. 5 indexed citations
9.
Zhang, Wenting, Xiaohui Wu, Pei Zhou, et al.. (2019). GDF5 Promotes White Adipose Tissue Thermogenesis via p38 MAPK Signaling Pathway. DNA and Cell Biology. 38(11). 1303–1312. 13 indexed citations
10.
Li, Gang, Zhi‐Sheng Ye, Cheng Shi, et al.. (2017). The Histone Methyltransferase Ash1l is Required for Epidermal Homeostasis in Mice. Scientific Reports. 7(1). 45401–45401. 26 indexed citations
11.
Chen, Shu, et al.. (2017). GenePANDA—a novel network-based gene prioritizing tool for complex diseases. Scientific Reports. 7(1). 43258–43258. 16 indexed citations
12.
Wang, Xiaowen, Herui Wang, Bin Guo, et al.. (2016). Gen1 and Eme1 Play Redundant Roles in DNA Repair and Meiotic Recombination in Mice. DNA and Cell Biology. 35(10). 585–590. 12 indexed citations
13.
Li, Shuang, Hong Tian, Chu Chen, et al.. (2016). Lmod2 piggyBac mutant mice exhibit dilated cardiomyopathy. Cell & Bioscience. 6(1). 38–38. 17 indexed citations
14.
Liu, Juan, Chaofeng Han, Bin Xie, et al.. (2014). Rhbdd3 controls autoimmunity by suppressing the production of IL-6 by dendritic cells via K27-linked ubiquitination of the regulator NEMO. Nature Immunology. 15(7). 612–622. 118 indexed citations
15.
Ding, Sheng, Tian Xu, & Xiaohui Wu. (2014). Generation of Genetically Engineered Mice by the piggyBac Transposon System. Methods in molecular biology. 1194. 171–185. 6 indexed citations
16.
Duan, Yanyu, Bertram Brenig, Xiaohui Wu, Jun Ren, & Lusheng Huang. (2013). The G32E Functional Variant Reduces Activity of PPARD by Nuclear Export and Post-Translational Modification in Pigs. PLoS ONE. 8(9). e75925–e75925. 9 indexed citations
17.
Zhang, Xiaochang, Kai Lei, Xiao‐bing Yuan, et al.. (2009). SUN1/2 and Syne/Nesprin-1/2 Complexes Connect Centrosome to the Nucleus during Neurogenesis and Neuronal Migration in Mice. Neuron. 64(2). 173–187. 373 indexed citations
18.
Xu, Rong, Kejing Deng, Yue Wu, et al.. (2008). A large-scale functional approach to uncover human genes and pathways in Drosophila. Cell Research. 18(11). 1114–1127. 18 indexed citations
19.
Yu, Juehua, Daniel A. Starr, Xiaohui Wu, et al.. (2005). The KASH domain protein MSP-300 plays an essential role in nuclear anchoring during Drosophila oogenesis. Developmental Biology. 289(2). 336–345. 59 indexed citations
20.
Wang, Guangxue, Gang Li, Min Han, et al.. (2005). Ubiquitous expression of mRFP1 in transgenic mice. genesis. 42(2). 86–90. 28 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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